Mask for changing the brightness profile of a photographic copy

ABSTRACT

Process for determining a mask for changing a brightness profile of a photographic copy with the following steps: photographic image data are derived from photographically recorded image information; optimized image data are obtained by correction of the photographic image data, wherein errors which were created to during the photographic recording of the image information are considered; a brightness mask, the values of which embody an influencing of the brightness profile of the photographic copy is determined based on the optimized image data.

FIELD OF THE INVENTION

[0001] The present invention relates to process for determining a maskfor changing the brightness profile of a photographic print or copyaccording to claim 1. Furthermore, the invention relates to a processfor changing the brightness profile during the manufacture of a print orcopy by way of the mask determined in accordance with the invention.Finally, the invention relates to an optical printer and a digitalprinter which use the mask determined in accordance with invention.

BACKGROUND ART

[0002] The term “photography”, as used herein, refers to the (permanent)recording of images produced by electromagnetic radiation (especiallylight) by means suited herefor (for example, a camera with film, adigital camera with CCD-chip, a film camera, a video camera, and thelike).

[0003] The field of the present invention relates to the computer and/oroptical processing of the photographic image information whichrepresents the picture produced. The photographic image information isthereby obtained, for example, by scanning a photographic master (forexample a film) and converted into digital image data. The photographicimage information can also be already present in digital format. It canthen be stored, for example, electronically (for example, CD-ROM, DVD),can be accessible through a network (for example LAN or Internet) or canbe recorded, for example, with a digital camera.

[0004] Photographic image data can be copied such as conventional imagedata onto a physical medium. For example, photographic paper serves asphysical medium onto which photographic films are exposed. The copyingcan also be carried out by way of a digital printer, which is controlledby the photographic image data, and onto normal paper or photographicpaper. However, the quality of the thereby achieved photographic printsis often unsatisfactory.

[0005] An essential reason for this is that the dynamics of theluminescence included in the image information to be copied cannot betransposed onto the copying medium. The reason for that is, for example,that photographic paper compared to a photographic film has a highlyreduced dynamic luminescence range. But also the dynamic luminescenceregion which can be illustrated with a printer is smaller than thetypical dynamic luminescence range of photographic image information.

[0006] The above-mentioned disadvantages encountered during the physicalrealization of a photographic copy have as a result that thesubjectively observed brightness profile during observation of the copyis negatively distinguished from the subjectively observed brightnessprofile of the photographic image information underlying of the copy.This means that the picture feel is not optimal for an average observerduring observation of the copy.

[0007] For example, brightness differences which often are stilldistinguishable for an observer of the original photographic imageinformation are no longer distinguishable for an observer of thephotographic copy when those brightness differences are found in a darkor very bright region of the photographic copy.

[0008] In order to overcome this disadvantage, masks were proposed whichcause a brightening or darkening of certain regions of the copy. Suchmasks are described, for example, in DE 19703063 A1 or in DE 4040498 A1.A calculated mask is used therein to control an LCD matrix. This LCDmatrix is found during the exposure of a photographic film onto aphotographic paper in the therefore required optical copying light pathand changes the brightness of the manufactured copy by region. Imagedata obtained from the original (photographic) image information areexclusively used for the calculation of the masks.

[0009] It is a disadvantage of the previous processes, that photographicerrors included in the original photographic image information, such ascolor errors or errors in the brightness distribution enter into thecalculation of the mask. The photographic errors can be caused, forexample, by errors during photography (underexposure or overexposure),specific film properties (color shifts caused by the film) or by thespectral sensitivity of the CCDs of the digital camera used.

[0010] However, when the photographic errors enter into the calculationof the matrix, no optimal manipulation of the brightness profile of thedesired photographic copy can be achieved.

SUMMARY OF THE INVENTION

[0011] It is accordingly an object of the invention to optimize thecalculation of a mask for the change of a brightness profile of aphotographic copy in such a way that negative effects of photographicerrors are suppressed.

[0012] The above object is achieved by the features of the independentclaims. Advantageous improvements are apparent from the dependentclaims.

[0013] A mask is calculated with the process in accordance with theinvention which is used for changing the brightness profile of aphotographic copy.

[0014] According to the process, photographic image data are firstderived from photographic image information, which includes the imageinformation to be copied, whereby preferably a reduction (associatedwith loss) of the image information content, especially the imageresolution, takes place. The photographic image information can includemore image information than is copied, for example, the photographicimage information can represent a sequence of images (for example, afilm with several individual pictures or a recording sequence of adigital camera), whereby in accordance with the invention the brightnessprofile of the copy of one of these images is changed or the maskrequired therefor is determined. The image information corresponding tothe remaining images can be used in accordance with invention fordetermination of the brightness mask (for example by way of completefilm analysis). Also, the image information of a whole image can beused, when only a section of the image is to be copied. The photographicimage information can be, for example, a photographic film (completefilm, individual picture). The photographic image data are preferablydigitalized during derivation from the photographic image informationand can be derived, for example, by scanning (for example of thecomplete film or of only an individual picture or a section thereof) andalternatively during further processing (for example data reductionand/or smoothing). However, the photographic image information can alsobe present in digital form, for example, when it originates from adigital camera or is transferred through a network, for example. Thephotographic image data can then be derived from these digital data, inthat, for example, the digitally available photographic imageinformation is taken over 1:1. However, an especially loss associateddata reduction, especially a resolution reduction, and/or smoothing iscarried out in order to minimize the subsequent calculation effort.

[0015] Overall it is preferred that the number of data which include thederived photographic image data (especially per individual picture), isabout 10,000 or less, preferably less than 2000 and especiallypreferably about 1000 (or less). Good results can be achieved inpractical use even with such a reduced data volume. The calculationeffort is simultaneously minimized. Especially for the generation ofphotographic image data by scanning an original film, one can choose anonly coarse scanning from the start so that the time required for thescanning process is significantly reduced compared to a fine scanning(as is common in the prior art) and the number of the photographic imagedata is at the same time reduced to the desired amount.

[0016] The reduction has the further advantage that finer details of thephotographic image information (of the photographic original or thescene illustrated thereby) have no influence on the masking. The alreadymentioned smoothing can also be of use for this purpose, whereby, forexample, the image data which are reduced during the derivation from theimage information to a desired number (for example in the form of areduced image matrix) are subjected to a low pass filtering. It isadvantageous in the case of color photo image data (for example acolored image matrix) to transform the color values into a color areawherein one of the axes describes the brightness of the image points. Ifthe color information is not used in the further processing (for examplefor the analysis), it is also sufficient to calculate gray values fromthe color values (for example, by weighted averaging), whichcharacterize the brightness of individual image points. The reductionand a matrix transformation connected therewith is described in detailin the EP 0475897. The disclosure of the reference EP 0475897 A1 isherewith incorporated into the present disclosure.

[0017] In accordance with the invention, the photographic image datawhich are preferably present in digital form are corrected in order toobtain optimized image data. Preferably, only that part of thephotographic image data is corrected and converted into optimized imagedata, which corresponds to image information to be copied or to aportion to be copied. During the correction, errors are considered whichwere generated during the photographic recording of the imageinformation. Optimized image data are thereby obtained which at leastapproximate the image data which are derived from an ideal photographicimage information, which represents the photographically recorded objectwithout error, which means corresponding to reality. Error-freerecording means especially that the photographically recorded imageinformation is free of color change. This means that the colors do notchange upon a variation of the photographically recorded light amountand with a constant spectrum, so that no color change is present.Especially photographic films exhibit color change.

[0018] A correction of the photographic image data can be carried out onthe basis of an analysis of an image sequence, as described or forexample, in EP 0586773, which is herewith incorporated into the presentdescription. The analysis of a whole film (“complete film analysis”) isdescribed in the EP 0586773. For example, the color change of a film isderived from the analysis results. The result of the analysis is thenused for the correction of the color dependent exposure.

[0019] If an image sequence analysis (for example, complete filmanalysis) is carried out in accordance with invention, in order torecognize the errors which were generated during the photographicrecording of the image information and to be able to take them intoconsideration, the photographic image data are derived from imageinformation which includes more than one individual picture. Then, forexample, the color values are analyzed, especially statisticallyanalyzed. A color area standardization (see also EP 0586773) is thencarried out for correction depending on the analysis results. This ispreferably achieved by a translation and rotation of the color area. Thetranslation thereby takes into consideration the mean coloring anddensity of the actual film and the rotation its exposure dependent colorchange (“tipping”). After standardization of the color area (i.e. thecorrection process), the image data are largely cleared of film baseddistortions (i.e. errors in the photographic image recording), so that,for example, ideally the same scene, when photographed with differentfilms, always leads to the same optimized image data. An image sequenceanalysis, especially with color area standardization derived therefrom,is important, since a large number of film products are on the marketwith sometimes significantly different image recording properties. Thisis also the case for the image recording properties of the differentdigital cameras.

[0020] In accordance with invention, alternatively or additionally otheranalysis types can also be selected apart from an image sequenceanalysis, in order to recognize the errors during image recording and tothen take them into consideration for the correction. For example, onecan revert back to stored data which include typical image recordingproperties of different films or digital cameras. The selection amongstdifferent stored data can, for example, be carried out by reference toinformation, which was additionally stored by the image informationcarrier (for example, film cartridge or diskette) apart from the imageinformation and, for example, regarding the film type or camera type orregarding the recording situation (artificial light or daylight) andwhich is also stored during the detection (recording) of thephotographic image information (for example, during photography) (forexample, data which are stored according to the Advanced Photo System orAPS).

[0021] With respect to the consideration of film specific data,reference is again made to EP 0586773 A1.

[0022] In addition to or in the alternative to the above analysismethods, an individual image analysis can be carried out. This meansthat the analysis is supported by the photographic or already optimizedimage data of an individual image which, for example, at leastessentially correspond to the image information to be recorded orinclude the image information to be recorded as an image portion. Ifonly the portion of an image is to be copied (for example, panoramicimage with APS), the analysis can be based, for example, on only theimage data which correspond to the portion, or in addition on image datawhich lie outside the portion, but are part of the recorded individualimage. The image attributes of an individual image are those propertiesof the image information representing an individual image, which can beextracted by individual image analysis from the photographic image dataderived therefrom. These image attributes describe especially thoseattributes which especially influence the picture feel (the sensoryperception). With such an analysis, especially the coloring, thecontrast, the exposure as well as the color, brightness and contrastprofiles are determined and examined. Furthermore, the analysis iscarried out especially for the recognition of color and/or brightnesserrors. Also, tipping phenomena (color differences between bright areasand shadows) should be recognized.

[0023] Preferably, the analysis of the photographic image data is usedfor classification of the image data. This means the photographic imagedata are assigned to a specific class of images. Possible image classesare, for example, counter light pictures, flashlight pictures,artificial light pictures, etc. However, classes can also be used whichcannot be translated directly into photographic terms in the art, in anyevent, the goal of the classification is the recognition of images withsimilar image attributes, especially with respect to contrast, exposure,coloring, etc.

[0024] Preferably, the individual attributes are combined into aN-dimensional attribute vector for the classification. The N-dimensionalattribute area is (for example, by way of a clustering process) dividedinto continuous regions, or by each region corresponds to a class. Theattribute vectors which fall within the same region originate from imageinformation with similar image properties and are assigned to the sameclass.

[0025] The individual image analysis can be carried out, for example, onthe basis of the photographic image data, in order to correct thephotographic image data and to achieve optimized image data or toparticipate in their determination, for example, depending on theclassification which took place. However, the individual image analysisis preferably carried out on the basis of the optimized image data.Preferably, the correction of the photographic image data and thedetermination of the optimized image data is in this case carried out onthe basis of an image sequence analysis or on the basis of storedtypical image recording data (or a combination thereof, see above).

[0026] The results of the individual image analysis are preferably sheused to modify the optimized image data. This modification is preferablycarried out in dependence of the classification result. The imageattributes obtained from the individual image analysis, or theclassification result can alternatively or additionally also enter intothe determination of the brightness mask from the optimized image dataand thereby modify the values of the brightness mask. Theabove-mentioned modifications are preferably carried out on the basis ofthe image attributes of an individual image, which were extracted fromthe optimized image data. However, they can also be carried out on thebasis of other attributes of the optimized image data, for example,attributes of an image sequence. This is especially then advantageouswhen an image series (for example, with sports pictures) was recorded orwhen the photographic image information was recorded, for example, witha video camera. A uniform copy quality can be achieved in this mannerfor the images of a series.

[0027] The correction of the photographic image data can be carried outin several ways, for example, pixel by pixel or by blocks using acorrection function. However, a correction transformation is preferablycarried out, whereby the fields recognized, for example, by theanalysis, are considered during the image recording or at leastapproximately compensated.

[0028] A translation and a rotation of the color area is preferablycarried out with this correction transformation. Optimized image dataare obtained with this correction transformation which is applied to thephotographic image data. If a copy is produced on the basis of suchoptimized image data, that copy is more aesthetically pleasing to anobserver than a copy based on the photographic image data. The optimizedimage data therefore have optimized image feel properties. Especially,irritating errors with respect to contrast, exposure and/or coloring arereduced. The correction transformation or a correction function can beoptimized for example, with respect to these errors in a stepwise,especially iterative process consisting of copying, analysis of thecopy, modification of the correction transformation, newly copying, etc.

[0029] In accordance with the invention the number of the optimizedimage data used as the basis for the mask calculation is preferablysignificantly reduced compared to the optimized image data eventuallyused as the basis for a photographic copy made with a digital printer.The former optimized image data can be derived from the latter optimizedimage data, for example, by a resolution reduction. However, theoptimized data for the mask calculation are in this case derived from analready strongly reduced number of data, in accordance with invention.

[0030] Based on the optimized image data (for the mask calculation)which have been cleared of photographic errors or wherein thephotographic errors have been at least minimized, a so-called brightnessmask is then produced. This brightness mask includes values by which thebrightness profile (the brightness distribution) of a photographic copyof the (original) photographic image information (for example, a film)is to be influenced.

[0031] The matrix so obtained can be, for example, stored or transferredfor further processing to a device (for example, an optical or digitalprinter), which produces a copy of the photographic image information.

[0032] If the photographic image information is present in physicalform, for example, as photographic film, the values of the brightnessmask can be used for control of a light density control device, forexample an LCD matrix. They can be especially used for control of theLCD device described in the European Application with the applicationNo. 98115693.8, the disclosure of which is herewith incorporated and acopy of which is attached.

[0033] The values of the brightness mask are, as already mentioned,determined from the optimized image data. One preferably proceeds insuch a way that first the gray values corresponding to these image dataare determined from the optimized image data and then the values for thebrightness mask are determined from those gray values.

[0034] The data processed by the process in accordance with inventionare preferably arranged in a matrix format and processed bytransformation of the matrices. Accordingly, the brightness mask ispreferably also arranged as a matrix.

[0035] The values of the brightness mask are preferably determined insuch a way that upon use of one region of the mask the brightnessprofile (the brightness distribution) of the photographic copy of thatregion of the photographic image information is influenced which alsoentered into the calculation of the mask region. Especially, regions inthe copy with average brightness should not be influenced or onlymarginally influenced. Furthermore, regions of low brightness should bebrightened (or remain unchanged) and/or regions with high brightnessshould be darkened (or remain unchanged). According to a preferredprocess, the brightening of dark regions is made dependent on the degreeof the darkness so that the brightening in very dark regions is againattenuated or no longer carried out. Accordingly, the darkening ofbright regions is preferably carried out such that the darkening in verybright regions is attenuated or possibly even completely left out.

[0036] In the just described exemplary embodiment of the brightness maskthe change of the brightness profile is thus carried out depending onthe brightness of the image data to be copied. More precisely, accordingto the present invention, the elements of the brightness mask arecalculated from the optimized image data and especially from thecorresponding gray values of the optimized image data. The calculatedvalues are preferably a function of the optimized image data or thecorresponding gray values. The function is preferably nonlinear. Thefunction can be present, for example, in the form of a table or it canbe realized as a programmed, partly linear function.

[0037] The function is preferably modeled so that it has the abovedescribed effect on the brightness profile of the photographic copy, forexample, the brightening of dark regions at the darkening of brightregions. The degree of brightening or darkening is thereby preferablylimited in such a way that upon copying or reproduction of the image novisible or irritating loss in total contrast occurs. Therefore, thealready obtained analysis results or especially information on thecontrast in regions of the image and/or the overall contrast preferablyenter into the modeling of the function or the calculation of the maskelements. This information is obtained, for example, by the abovedescribed analysis which determines the characteristics of thephotographic image data. In addition, or alternatively, a separateanalysis of the optimized image data can be carried out from which thecharacteristics of the optimized image data are then derived which thenenter into the calculation of the mask elements.

[0038] Furthermore, the degree of brightening or darkening is preferablylimited so that the visibility of the noise, for example, thegranularity, if the photographic image information is a negative film,is not excessively increased in the dark and or bright portions of theimage. In order to determine the degree of limitation of the brighteningor darkening, one can again go back to characteristics which weredetermined during the analysis of the photographic image data or duringa separate analysis of the optimized image data (for example,overexposed, underexposed, etc.). Furthermore, information on the filmtype (for example, ASA No. regarding the granularity) or the photographsituation (for example, taken with flash) can enter into thedetermination of the function.

[0039] During the realization of the function, the limiting of thebrightening or darkening can be carried out,; for example, by setting amaximum value. The maximum value in turn can be a function of thespecific characteristics of the photographic image information (forexample, film type) or the specific characteristics of the photographicimage data or the optimized image data (for example, total contrast).

[0040] The function is preferably modeled in such a way that nodistortion due to image unrelated brightness jumps occurs during themasking. This means that the function to be used is preferably constantand that the slope of the function cannot be too large. It can beadvantageous for this purpose to subject the brightness mask to asmoothing or to subject the matrix underlying the brightness mask to alow pass filtering.

[0041] As already mentioned above, specific characteristics or otherwiserecorded characteristics or information (for example, data stored inaddition to the image information during the image recording, especiallydata regarding the photograph situation or, for example, the camera typeof a digital camera or the film type) can enter into the determinationof a best suited function by the analysis of the image data. It isthereby advantageous to assign the different characteristics todifferent classes depending on the degree of their distinction. The bestsuited function is then again assigned to each class. The classformation and the function modeling for each class can then be refinedwith increasing experience level, for example, by way of an expertsystem.

[0042] Apart from the consideration of global properties, which areexpressed in the image classes, it is also advantageous to considerlocal properties in the vicinity of a masking point. As describedfurther below, a local control of the masking strength is preferablycarried out herefor.

[0043] A local control of the masking strength is necessary, because,for example, it can lead to irritating effects when the brightness maskis superimposed with the image information used for the copy. Thisapplies especially where the brightness profile of the image informationto be copied has large jumps. For example, if a brightness step with asteep step flank of the image information to be copied is superimposedwith an inverse brightness step with flat step flank of the mask, anedge superelevation can occur both in the positive as well as thenegative direction. This means that at a step transition from dark tobright initially a normally dark value is present which then shortlybefore the step further darkens and then immediately after the stepstrongly brightens. The strong brightening is shortly thereafter reducedagain to a normal bright value. Because of the low dynamic range of thephotographic paper, the stronger darkening is normally not visible incontrast to the stronger brightening. For this reason, visible edgesuperelevation effects are preferably moved into such regions wherein anedge superelevation is not conspicuous for the observer. In the abovedescribed case, a mask would be structured such that an edgesuperelevation occurs only in the dark region (albeit stronger) and thatno edge superelevation occurs in the bright region. The position of thestep flank of the brightness mask is thereby changed in directiontowards the darker region of the brightness step to be copied until itis completely located in the dark region.

[0044] In order to avoid undesired effects during the superimposition,for example, as are described above, the masking strength is controlledwith local resolution in that preferably the values of the elements ofthe brightness mask are changed. The control is thereby preferablycarried out such that the values in a local control region whichincludes an actual mask element and further mask elements are made thebasis of the calculation from which a new value for the actual maskelements results.

[0045] Different nominal values or functions can be used during thecalculation for the local control the results of which can be, forexample, weighted and combined with one another. For example, themaximum value determination, the minimum value determination, the mainvalue determination, the mean determination can be used as functionswhich are then preferably applied to the values in the mentionedmanipulation region. However, the function for the determination of thestandard deviation, of the detail contrast, etc. can also be used. Ifone uses only, for example, a minimum function, this results in the“careful” masking of the regions with higher mask values, which is equalto the flank displacement described above by example. In accordance withthe invention, characteristics of the image recording (for example, filmtype, ASA number, etc.) and/or specific characteristics of thephotographic image data and/or the optimized image data also enter intothe determination of the type of the manipulation or the setting of theabove-mentioned weighting during the manipulation of the values of thebrightness mask. One can in this case also classify or go back to analready carried out classification. As already mentioned above, themanipulation functions (maximum function, minimum function, etc.) can bedifferently weighted during the determination of a new mask value. Thestructure of the weights can thereby be made dependent, for example,from the class specified.

[0046] The manipulation and thereby, for example, the structure of theweights can however also be made dependent from the properties(characteristics) of the different local regions of an individual image.Expressed otherwise, values of the brightness mask which concern regionsof the copy with different characteristics or properties are differentlymanipulated. One property of the region represents, for example, it'sinformation content (“energy density”). For example, information richimage regions typically have strong light/dark variations. Preferably,the manipulation is carried out such a way that information poor imageregions are not masked or masked less strongly than information richimage regions. Image regions with different properties or attributes arerecognized, for example, by way of a “local analysis” with which locallyresolved regions of an image can be analyzed. This local analysis isbased on, for example, a locally resolved light/dark analysis, andanalysis of the light/dark variations or the contrast variations. Themanipulation is carried out preferably locally differently depending onthe local properties or characteristics of the image, especially a valueof a brightness mask is manipulated depending on the characteristics(image characteristics) of an image region locally assigned to thevalue.

[0047] The local analysis/manipulation itself can be based on ananalysis/manipulation of the photographic image data, optimized imagedata or the values of the brightness mask itself Especially in thelatter case, the analysis is preferably an integrated part of thecalculation of a manipulated (modified) brightness mask (see furtherbelow, for example, the use of the standard deviation function). Thelocal manipulation (modification) is preferably carried out such thatthe influencing of the brightness profile is locally “dosed” or variedso that locally a more or less strong influencing of the brightnessprofile results and depending on the locally assigned image attributes(attributes of the locally assigned image region).

[0048] To superimpose the brightness mask with the image information tobe copied, it can be desired that the mask has a preselected number ofelements. If the mask is present in matrix form, the matrix can be, forexample, reduced or enlarged, in order to achieve an adaptation to thedesired number or to a desired number of lines and columns.

[0049] Adaptation to a preselected number is especially thenadvantageous when a light control arrangement, for example, an LCDmatrix, is controlled with the mask values during the exposure of a filmonto a photographic paper. Such an LCD matrix has a preselected numberof elements.

[0050] In the case in which the number of the mask elements is to beadapted, the determination of the brightness mask is preferably carriedto in two steps. First, a first mask is calculated, which is to cause abrightening or darkening. This mask is preferably a matrix with the samedimensions as a matrix in which the optimized image data areillustrated. A second matrix with a fitting number of elements and withthe desired number of lines and columns is then determined from thefirst mask. If one considers, for example, an actual element of thefirst mask, which is located in an assigned region, the values of theelements in this region are used as a basis for the manipulation of thevalue of the actual element and the value which results from themanipulation is assigned to that element of the second mask, which isassigned to the actual element of the first mask.

[0051] When, as discussed above, the local properties or actual units ofan image are analyzed and if the manipulation is locally differentdepending on the local properties, the local properties or attributes ofthat region of the first mask are preferably considered for thecalculation of each element of the second mask which is associated withthat element. This applies especially when the first as well as thesecond mask are expressed in matrix format.

[0052] In the case of an optical masking, an optical mask (for example,a liquid crystal matrix or light control arrangement) is controlled withthe values of the brightness mask calculated preferably in two steps(first mask and second mask). The optical mask is thereby preferablypositioned at a certain distance from the plane of the original so thatan unfocused image of the mask (unfocused overlay) results. Thedimensions of the brightness mask are preferably selected to be equal toor at least about the same as the number of the lines and columns of theoptical mask matrix.

[0053] In the different steps of the calculation of the brightness mask,one preferably insures that the geometrical assignment of the matrixpoints or mask points remains in tact. This means especially thatneighboring mask values of a mask value can be traced back toneighboring regions of the photographic image information underlying themask value (while maintaining the orientation) so that the brightnessmask and the image information to be copied are properly superimposed inthe optical system.

[0054] In general, the image information to be copied can be the same asthe photographic image information or arises therefrom throughprocessing. In an optical system, the processing can be carried out, forexample, by manipulation of the exposure through color filters, so thatthe (original) photographic image information (information of thephotographic film) differs after the filtering from the film informationto be copied, which is then superimposed with the mask.

[0055] This applies correspondingly for superimposition in a processor.There, the photographic image information is often digitally present inhigh-resolution. This digital image information is, as alreadymentioned, preferably reduced in a first step of the process inaccordance with the invention for the determination of the brightnessmask (derivation of the photographic image data). However, for thedetermination of the image information to be copied no reduction orpreferably only a small reduction is carried out. But preferably theprocessing step is a correction transformation (see EP 0586773 A1). Theimage information obtained after the correction transformation is thenthe image information to be copied, which is to be superimposed with thebrightness mask (in a processor).

[0056] The masking in a processor is preferably carried out digitally orelectronically. The brightness mask (in the two-step process the secondmask) is thereby transformed by way of one of the known interpolationprocesses (for example, “image resampling”, “image resizing”, “upsampling” . . . ) into an image with the resolution of the imageinformation to be copied, preferably smoothed by way of a low passfiltering (preferably during or after the interpolation) andsubsequently superimposed in a processor with the original image matrix.A preselected connection function is selected, for example, simpleaddition, for the superimposition in the processor. If the mentionedsmoothing is carried out, this process corresponds to the unfocusedprojection in the case of the optical masking.

[0057] As mentioned above, the brightness mask is preferably derivedfrom the gray values, which are in turn determined from the optimizedimage data. However, the brightness mask can also be calculatedrespectively separately for the processing of image information ofdifferent color to be copied (for example, for the red, green and blueexposure). Those brightness values of the optimized image data which areassigned to a specific color are thereby preferably used for thecalculation of the brightness matrix intended for the correspondingcolor. If only one mask is used, the color information included in theoptimized image data can also be taken into consideration.

BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Exemplary embodiments of the present invention are described inthe following. Further preferred features are thereby disclosed.Different features of different embodiments can be combined with oneanother.

[0059]FIG. 1a shows a schematic cross-section of the construction of anexposure device with a light density control arrangement which iscontrolled with the values of the brightness matrix in accordance withthe invention;

[0060]FIG. 1b shows the optical lengths during the copying;

[0061]FIG. 2 shows an exemplary function for the calculation of themask;

[0062]FIG. 3 schematically shows geometric transformations which arecarried out for the calculation of the mask;

[0063]FIG. 4 shows an exemplary assignment process at a transition fromthe first mask to the second mask;

[0064]FIG. 5 shows a signal and data flow diagram with an opticalprinter; and

[0065]FIG. 6 shows a data and signal flow diagram in a digital printer.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

[0066] An exposure arrangement 10 is generally illustrated in FIG. 1which includes an LCD arrangement 20 which is controlled with the valuesof the brightness matrix. Not illustrated are the optical arrangements(filter), which serve the control of the exposure in the three colorsred, green and blue.

[0067] The liquid crystal matrix is positioned at a suitable distancefrom the plane of the film.

[0068] A light beam originating from a light source 12 is shone by wayof an optical arrangement 14,16, and along the optical axis 18 through amaterial band of negatives 21. The LCD arrangement 20 with the featuresaccording to the invention is positioned before the negative 21.

[0069] The LCD arrangement 20 shown above right and enlarged in FIG. 1has darkened regions 20 b which leads to a larger light scattering sothat less light is captured by the lens 22 in this region. Conversely,regions 20 a are present, which are only little or not at all darkenedor only over a short time period. Correspondingly, the opposite side 20b of the LCD arrangement 20 can be darkened over a longer time.

[0070] The light passing through the LCD arrangement 20 subsequentlyshines through the negatives 21 and is projected by the optic 22 onto apaper photo 26 of a band 24 with photo sensitive material. The curve 28.above the copy 26 here indicates the course of the light intensityacross the copy 26, when the LCD arrangement 20 is not scattering. Thecontinuous line 30 indicates the intensity course of the light when theLCD arrangement, as shown a top right in FIG. 1, is operated in anasynchronous scattering mode. Accordingly, the curve 30 is asymmetricalor distorted one-sided according to the light-dark-graduation of the LCDarrangement 20 above the material band 24 or above the copy 26 to beexposed.

[0071] The optical lengths occurring during the exposure are illustratedin FIG. 1. The following correlations apply: $\begin{matrix}{\frac{D}{2H} = {{{tg}\quad \alpha \quad {numeric}\quad {aperture}} \approx {0.07\quad \left( {\alpha \approx 4^{\prime}} \right)}}} \\{\frac{B}{2H} = {{tg}\quad \beta \quad {numeric}\quad {image}\quad {aperture}}} \\{\frac{h}{H} = {\frac{d}{D}\quad {defocusing}}} \\{\frac{d}{B} = {\frac{h\quad {tg}\quad \alpha}{H\quad {tg}\quad \beta}\quad {lack}\quad {of}\quad {focus}\quad \left( {\approx 0.1} \right)}}\end{matrix}$

[0072] The liquid crystal matrix is positioned at a suitable distance hfrom the film plane, and a distance H exists between the pupil of thelens 22 shown in FIG. 1a and the liquid crystal.

[0073] A liquid crystal matrix can consist, for example, of 20×30 cells.The outer elements of the matrix are preferably outwardly broadened inorder to catch impreciseness in the positioning and a certainvariability of the optical enlargement as well as to avoid optical edgeeffects. The active surface of the matrix is, for example, 33 mm×48 mm.The distance h between the liquid crystal and the plane of the film isselected such that with exact positioning, at the most importantenlargement and, for example, in the case of a 35 mm negative (fullformat, nominal dimension of the negative 24 mm by 36 mm), the centralregion of the liquid crystal which is 30 mm×45 mm large (20×30 squarecells) is active as optical mask. The distance guarantees the requiredlack of focus of the mask projection onto the photographic paper.

[0074] A printer which uses the mask calculation principal in accordancewith invention is, for example, equipped with two scanners, a colorscanner with, for example, a resolution of 260×390 and a density scannerwith, for example, a resolution of 260×390 image points, whereby theresolution is respectively per photographic image information to beprocessed (for example, per individual film negative). Both scannerspreferably measure the negative image over its whole image surface (24mm×36 mm) on a homogeneous raster (Δx=Δy).

[0075] Principally, the image matrices which were obtained through thecolor scanner as well as the image matrices which were obtained throughthe density scanner can be used as starting points for the maskcalculation and therefore serve as photographic image data. The imagematrices of the color scanner are already present in a sufficiently lowresolution so that the reduction of the image information present indigitized form can be left out and the digital image informationdirectly used as photographic image data in the calculation of the mask.

[0076] Although on the one hand the calculation cost for the maskcalculation increases when the image matrices of the density scanner areused, more freedom is available on the other hand in the selection ofthe dimensions (M₂×N₂) of the photographic image data arranged in amatrix. For general, if the information, which is obtained from thedensity scanner is present in an M₁×N₁ -matrix, one can change to areduced matrix by a reduction transformation with the dimensions M₂×N₂.This reduced matrix that includes the photographic image data which areto be used as a basis for the further processing for the maskcalculation.

[0077] In a preferred embodiment, the photographic image data are formedby the reduced image matrix of the color scanner, since the latter atthe same time forms a basis for a whole film or individual imageanalysis, as is disclosed, for example, in the above-mentioned EP0586773.

[0078] As already mentioned, the photographic image data obtainedthereof are subjected to a correction transformation in order to obtainthe optimized image data. Gray values are then preferably producedtherefrom.

[0079] In the case of a colored photographic image information (coloredimage matrix, the color values are preferably transformed into any colorspace wherein one of the axes describes the brightness of the imagepoints in order to obtain therefrom the photographic image data to bederived from the photographic image information. If the colorinformation is not further used (for example, for the analysis) it isalso sufficient to calculate gray values from the color values (forexample, by weighted averaging) which characterize the brightness ofindividual image points.

[0080]FIG. 2 shows possible functions for the calculation of the grayvalues into values for a first mask matrix. The second mask matrix isthen formed from the first matrix in the later step, which is then equalto the brightness mask which is superimposed onto the film informationto be copied.

[0081] In FIG. 2, the brightness D of the gray values of the optimizedimage data (in the following referred to as “optimized gray values”) isplotted on the abscissa. Since bright points in the desired photographiccopy correspond to high densities of the negative, D can be considered astandardized (corrected) film density or negative density. In theselected illustration, the (corrected or optimized) value D=0corresponds to a “normal” or “mean” brightness in the photographic copy(when no masking is carried out), while positive values of D correspondto brighter regions and negative values of D correspond to darkerregions in the photographic copy (when no masking is carried out). Theordinata on the other hand illustrates the “optical density” K of themask. Positive values of K cause a brightening in the photographic copy,negative values a darkening compared to an unmasked copying process. Forthe physical realization of the optical mask, the passive mask ispreferably used rather than an active mask (for example, LED matrix).The darkening of the lights (negative branch of the characteristic linesin FIG. 2) must in this case with a negative film be achieved bylonger/more intense exposure.

[0082] The characteristic lines in FIG. 2A corresponds to theconventional unfocused masking, whereby in addition a limiting of themask upwardly and outwardly takes place. The strength of the masking isinfluenced by way of the steepness S of the characteristic line and thelimiting values K_(max), K_(min) of the mask density. In general, is isadvantageous to use the masking only for pronounced shadows and brighterregions in the image; a corresponding characteristic line is illustratedin FIG. 2B. A masking occurs only when the standardized film densityexceeds the value D+ or falls below the value D−.

[0083] One can be satisfied with only brightening the shadows andleaving the light areas unchanged, which can be achieved with acharacteristic line according to FIG. 2C. The advantage of this choiceconsists in that the masking does not cause an increase in the exposuretimes (and therefore no reduction in the printer throughput).

[0084] For aesthetic reasons, shadow regions which include little imageinformation are not or only slightly masked. This is achieved with thecharacteristic line of FIG. 2D in that the masking is attenuatedstarting at a selectable threshold D^(fm) with increasing approaching ofthe negative density to the film mask.

[0085] A number of picture categories are present wherein a masking canbe disadvantageous. Examples are night photographs and sunsets whereinthe maximum density of the photographic paper is not to be reduced inany case. This can be achieved partially with the characteristic line ofFIG. 2D. However, such pictures are preferably completely excluded froma masking. For this purpose, the fact can be used that the imageanalysis provides a classification of the photographic image information(negative) according to its image content. Night photographs and sunsetsaccumulate thereby in specific classes which can be excluded from amasking. More generally, is also possible to optimize the maskingindividually for each image class through the different characteristicline parameters illustrated in FIG. 2 (S, K_(max), K_(min), D+, D−,D^(fm)).

[0086] In accordance with invention, the masking can be selectivelyattenuated or strengthened depending on the character of thephotographic image information or the photographic image data and/or theimage recording (for example, film type, stored information about theimage recording, for example, photograph with or without flash, etc.),or depending on the classes.

[0087] The first masks calculated according to the above process canalso be further processed. Especially a further smoothing can beadvantageous, which further supports the already mentioned blurriness.

[0088]FIG. 3 schematically illustrates the geometric transformationsused in the transformation of a matrix into another matrix. Theillustrated image matrix thereby corresponds to the photographic imageinformation and the illustrated reduced image matrix to the photographicimage data.

[0089] On a basis of the known geometric relationships (distance of theplane of the film from the pupil of the lens, distance between film andmask planes) as well as the knowledge of a possible displacement of thephysical center of the mask relative to the projection axes a pointP_(o) in the film plane with the coordinates (x₀,y₀) can be obtainedcorresponding to each point P₁ in the mask plane with coordinates(x₁,y₁) (and vice versa). On the basis of the knowledge of the scannerresolution in the x₀ and y₀ direction, the mask a resolution in the x₁and y₁, direction and the knowledge of the reduction factorsM₁/M₂,N₁/N₂, M₂/M₃, N₂/N₃ an “assigned element” can be determined for eachelement in one of the matrices as well as an assigned environment(assigned region) in the other three matrices. It is hereby pointed outthat the dimension M₁, N₁, is the dimension of the reduced digital imagedata. A matrix with the dimensionM₂×N₂ represents the (reduced)photographic image data which form the basis of the mask calculation.The dimension of the first mask is also preferably equal to M₂×N₂. Thedimension of the second mask derived from the first mask is M₃×N₃.

[0090]FIG. 4 shows an example how an “associated environment”(associated region or manipulation region) is determined. Thisdetermination is preferably carried out to achieve a calculation of thefirst mask matrix (first mask) into the second mask matrix (secondmask).

[0091] A locally different manipulation of the brightness mask ispreferably achieved such that the properties or attributes of theassociated environment (the assigned region) of the first matrix aretaken into consideration for the calculation of each element of thesecond mask matrix.

[0092] The geometric center (P or Q) of an element of the second mask isfirst determined for the assignment. The element of the second mask canbe assigned to an element of the first mask of a basis of thecoordinates of this point, as illustrated in the figure. Thedetermination of the “assigned environment” is carried out on the basisof the distances of P (or Q) from the geometric center points of theneighboring elements of the first mask matrix. One distinguishes betweentwo cases:

[0093] If P (or Q) lies within the hatched elevated square in theassociated pixel, the “assigned environment” consists of five elementsof the first mask matrix as shown on the left side in FIG. 4.

[0094] If Q (or P) lies outside of the mentioned square, the “associatedenvironment” consists of four elements of the first mask matrix isillustrated on the right side of FIG. 4.

[0095] In both cases, the “assigned environment” are the (four or five)elements of the first mask matrix with the smallest distance of thegeometric centers to P or Q.

[0096] And efficient calculation of the second matrix from the firstmatrix is preferably achieved with a table calculated in advance, whichfor each element of the second mask matrix includes the number and theindices of the elements of the “assigned environment” in the first maskmatrix. The special cases which are generated at the edge of thematrices can be elegantly considered with such a table.

[0097]FIG. 5 illustrates the data and signal flow was in the case ofoptical photographic printer which uses a negative film as copyingoriginal (photographic image information).

[0098] The input image matrix has a resolution of 26×39 so that areduction step is obviated. The color data are already present in thecolor area in which one of the axes describes the brightness. They aredetermined from the spectral measured data by way of the “KarhunenLoeve” transformation as described in EP 0475897. First, a film specificcorrection transformation is determined on the basis of the measureddata of the whole film, as described in EP 0586773. The image matrices(photographic image data) which are subjected to this transformation(“color space standardization”) are individually analyzed andclassified. The image corrections resulting from this analysis are onthe one hand applied to the standardized image matrices and on the otherhand serve the determination of the exposure values with which thecorresponding negative is to be copied. The image matrix (optimizedimage data) subjected to the film specific and image specific correctionis now used for the calculation of the first mask matrix. An optimizedfunction F(x) for an image class determined on the basis of theindividual image analysis is used which preferably causes the desiredbrightness changes.

[0099] The second mask matrix is calculated in a subsequent step. Asecond element X₂(i₀,j₀) of the second mask matrix can be calculated asfollows from the elements X₁(m,n) of the first mask matrix:

[0100] Let U(i₀,j₀) be a region of the matrix X₁ assigned to the elementX₂(i₀,j₀), for example, U(i₀,j₀)={(m₀,n₀), (m₀+1,n₀), (m₀−1,n₀),(m₀,n₀+1), (m₀,n₀−1), (m₀+1,n₀+1), (m₀+1n₀−1), (m₀−1n₀−1), (m₀−1,n₀−1),and N(i_(0,)j₀) the number of elements in U(i₀,j₀).

Max(i ₀ ,j ₀)=Max(X1(m,n)εU(i ₀ ,j ₀)}:

[0101] (Maximum of the elements of X₁ in the region U

Min(i ₀ ,j ₀)=Max(X1(m,n)εU(i ₀ ,j ₀)}:

[0102] Minimum of the elements of X₁ in the region U

Mean(i ₀ ,j ₀)=ΣX1(m,n)/N(i ₀ ,j ₀) (m,n)εU(i ₀ ,j ₀):

[0103] Mean of the elements of X₁ in the region U (instead of the normalmean, a weighted mean with low pass effect can also be used)

Med(i ₀ ,j ₀)=Median {X1)(m,n), (m,n)εU(i ₀ ,j ₀):

[0104] Mean of the elements of X₁ in the region U (in the region U thereare (about) the same amount of elements of X₁ is smaller than largerthan “Med”)

[0105] Then, the following formula can be used for the calculation ofX₂:

X₂(i₀,j₀)=α_(Max)*MaX(i₀,j₀)+α_(Min)*Min(i₀,j₀)+α_(Means)*Mean(i₀,j₀)+α_(Med)*Med(i₀,j₀)(with α_(Max), α_(Min), α_(Mean), α_(Med)≧0 andα_(Max)+α_(Min)+α_(Means)+α_(Med)=1).

[0106] The above-mentioned parameters α_(Max), α_(Min), α_(Mean),α_(Med) are preferably selected depending on the class in order toobtain an optimum result.

[0107] The above described functions Mean and Median correspond to asmoothing. For example, if the standard deviation is used as function,then that is a measure for the detail contrast. With the standarddeviation can be achieved that regions with little image information areless strongly masked. The function Minimum causes a “cautious” masking.It can be used for the prevention of irritating side effects (excessiveedge variations) which can occur upon strong masking. The use of thestandard deviation function therefore causes different manipulations ofthe values of the brightness mask depending on the local properties ofthe image (lower or higher information content). The function Maximumcan be used for the reduction of excessive edge variations.

[0108] Before a liquid crystal matrix can be controlled through an LCDcontrol electronic with the mask values obtained therewith, the maskvalues are preferably further corrected. Correction tables arepreferably provided therefor. With the correction, inhomogeneities inthe brightness profile of the photographic copy caused by the opticalcopying or the optical arrangement (especially as schematically shown inFIG. 1a) are considered. However, inhomogeneities caused by the copymedium (photographic paper) or properties specific for the median usedcan also be considered. Especially, local inhomogeneities of the liquidcrystal matrix and inhomogeneities upon illumination in the exposureplane or copying plane as well as especially the specific voltagetransmission curve of the liquid crystal are considered. The LCD controlelectronic is then controlled with these corrected mask values.

[0109]FIG. 6 image dates the data and signal floats in the case ofadditional printer, where in all sole negatives are used as the copymasters (photographic image information).

[0110] As far as the same function blocks are used in FIG. 6 as in FIG.5, reference is made to the description of FIG. 5. Differences betweenFIGS. 5 and 6 exist in the units specific for the optical copying, suchas the illumination calculation and to the control of the LCD.

[0111] The photographic image information which goes into FIG. 6 ispresent in the form of a color and high-resolution matrix (in RGB form).This image matrix is preferably initially transformed into a color areain which one of the axes describes the brightness. The image matrix sotransformed is reduced to a lower resolution for the purpose of filmanalysis, image analysis and mask calculation. The reduced image matrix(photographic image data) has now properties which are comparable withthe one of the entry image matrix in FIG. 5.

[0112] The corrections resulting from the analysis are not only used forthe mask calculation but also preferably used for the correction of thehigh-resolution image matrix (correction transformation).

[0113] The second mask matrix is determined as described herein. It isinflated to a high-resolution which is superimposed with the imagematrix by way of interpolation and low pass filtering.

[0114] The described invention relates also to software or to a program(especially compiled software) for the execution of the process inaccordance of the invention as well as a computer readable storagemedium (CD-ROM, DVD, diskette, hard drive, etc.) with the software inaccordance for the invention stored thereon.

1. Process for determining a mask for changing the brightness profile ofa photographic copy, comprising the steps of: a) deriving photographicimage data from photographically recorded image information; b)obtaining optimized image data by correction of the photographic imagedata, whereby errors which were created during the photographicrecording of the image information are considered; c) a brightness mask,the values of which embody an influencing of the brightness profile ofthe photographic copy, is determined based on the optimized image data.2. Process according to claim 1, including the further steps ofextracting attributes from the optimized image data for analysis of theoptimized image data, and modifying the optimized image data before stepc) and/or modifying the values of the brightness matrix in step c)depending on the extracted attributes.
 3. Process according to claim 2,wherein the image information to be copied is classified, based on theextracted attributes and the modification is carried out depending onthe classification result.
 4. Process according to claim 1, wherein thevalues of the brightness mask are modified depending on attributes ofone region of the photographic image data, optimized image data and/orthe brightness mask associated with the respective local value. 5.Process according to claim 1, wherein gray values are determined in stepb) which correspond to the optimized image data and which are thenreferred to for the determination of the brightness matrix.
 6. Processaccording to claim 1, wherein a brightening of darker regions caused bythe brightness matrix is no longer carried out or is attenuated, whenthe degree of darkness exceeds a preselected threshold.
 7. Processaccording to claim 1, wherein in step c) only one mask value is assignedto each optimized image datum, from which the brightness mask is thendetermined.
 8. Process according to claim 7, wherein the assigned maskvalues form matrix elements of a first mask matrix and the second maskmatrix is calculated from the first mask matrix, whereby a matrixelement of the first mask matrix is assigned to each matrix element ofthe second mask matrix and the value of each matrix element of thesecond mask matrix is calculated from those of the matrix elements ofthe first mask matrix which are included in an associated region of thefirst mask matrix and which includes the assigned matrix element andmatrix elements surrounding the assigned matrix element, whereby thefirst mask matrix forms the brightness mask.
 9. Process according toclaim 8, wherein for the calculation of each element of the second maskmatrix the attributes of the region of the first mask matrix assigned tothe element are considered.
 10. Process according to claim 1, whereinthe derivation of the photographic image data according to step a)includes a loss associated reduction of the data volume.
 11. Processaccording to claim 1, wherein the number of mask values is less than2000, preferably about
 1000. 12. Process for changing the brightnessprofile of a photographic copy, wherein a photographic copy is producedbased on photographic image information and a brightness mask iscalculated according to the process of claim 1 and that the brightnessmask is superimposed with the image information to be copied forinfluencing the brightness profile of the photographic copy.
 13. Processaccording to claim 12, wherein the superimposition is carried outoptically with a light density control arrangement which controls thelight density, resolved by area in the different regions of the copy tobe produced and during the exposure of the copy material, by controllingthe light density control arrangement based on the values of thebrightness matrix.
 14. Process according to claim 12, wherein thesuperimposition is carried out in a computer and the calculated resultis used for the control of a printout of the photographic copy. 15.Optical printer for the manufacture of photographic copies, with a lightdensity control arrangement with which the light density, resolved byarea, is controllable in different regions of a photographic copy to bemade during exposure of the photographic copy material, with a digitaldata processing device which determines a brightness mask according tothe process of claim 1 and controls the light density control devicewith the values of the brightness mask.
 16. Digital printer for theprinting of photographic copies based on digital photographic imageinformation, with a printing device for forming a photographic copy onthe basis of the digital photographic image information, with a dataprocessing device which determines a brightness mask from the digitalphotographic image information according to the process of claim 1 andwhich superimposes the values of the determined brightness mask withadditional photographic image information in a computer, whereby theresult of the superimposition is printed out by the printing device.